With the advent of sophisticated medical imaging modalities, such as Computed Tomography (CT), three-dimensional (3-D) volumetric data sets can be reconstructed from a series of two-dimensional (2-D) X-ray slices of an anatomical structure taken around an axis of rotation. Such 3-D volumetric data may be displayed using volume rendering techniques so as to allow a physician to view any point inside the anatomical structure, without the need to insert an instrument inside the patient's body.
One exemplary use of medical imaging is in the area of preventive medicine. For example, CT colonography (also known as virtual colonoscopy) is a valuable tool for early detection of colonic polyps that may later develop into colon cancer (or colorectal cancer). Studies have shown that early detection and removal of precursor polyps effectively prevent colon cancer. CT colonography uses CT scanning to obtain volume image data that represents the interior view of the colon (or large intestine). It is minimally invasive and more comfortable for patients than traditional optical colonoscopy. From CT image acquisitions of the patient's abdomen, the radiologist can inspect any suspicious polyps attached to the colon wail by examining reconstructions of individual planes of the image data or performing a virtual fly-through of the interior of the colon from the rectum to the cecum, thereby simulating a manual optical colonoscopy.
Both two-dimensional (2-D) and three-dimensional (3-D) views are often provided in CT colonography. 2-D views are typically cross-sectional representations of intensities occurring at a given slice. These 2-D images may be presented in the axial, coronal and sagittal planes. 3-D views present images with a volumetric appearance, similar to an optical colonoscopy. Although 3-D views allow the user to examine and detect any bumps on the colon walls, it is often very difficult to differentiate between true polyps and irrelevant structures such as residual stools or lipomas. 2-D views, on the other hand, provide the voxel intensities necessary to discriminate between these structures.
The problem with 2-D views, however, is that polyps behind or on the haustral folds are often missed because the haustral folds change their shapes drastically according to which cross sections are viewed. In many cases, polyps are dismissed as irrelevant when several cross-sectional images are examined, because the folds quickly move away when the slices to be viewed are changed. As a result, inspecting each fold is extremely time-consuming, and polyps occurring on the folds are very difficult to detect. Accordingly, the accuracy and sensitivity of computer-aided diagnosis and treatment of colon cancer are severely impaired by these shortcomings of conventional systems.